Do you want to publish a course? Click here

Developing A Comprehensive Accident Report Template For Syria And Evaluating The Limitation In The Currently

تقييم نقص بيانات الحوادث المرورية في سورية من خلال تطوير استمارة تفصيلية للحادث المروري

1187   1   18   0 ( 0 )
 Publication date 2016
  fields Civil Engineering
and research's language is العربية
 Created by Shamra Editor




Ask ChatGPT about the research

The primary objective of this research is to assess the state of the road accidents’ data currently collected by using traditional text reports in the Syrian Arab Republic. The followed approach consisted of two main steps: (1) Developing a comprehensive road accident report template which contains all data items that should collected from a road accident . (2) Digitizing data from randomly selected traditional road accident text reports into a computer database developed based on the accident report template established in step 1.

References used
BECKMANN.J , 2006 - Road Accident Data In The Enlarged European Union. European Transport Safety Council , Belgium , 40 P
PEREZ.C, 2007 - Urban Traffic Accident data collection and analysis in Europe: Survey study . Botanical Garden of the University of Valencia , Spain , 31 P
DaCoTA , 2012 – Annual Statistical Report 2012 . European Road Safety Observatory , European Union , 86 P
THE NATIONAL ACADEMIES , 2011 -Achieving Traffic Safety Goals in the United States . Transportation Research Board ,Washington , 262 P
rate research

Read More

The objective of this research is to measure and evaluating the quality of service in the private commercial banks in Syria and for the purpose of determining the basic dimensions of quality of service that customers are looking for and preferred, even these banks are able to focus and emphasize it and use it to enhance customer satisfaction and retention, and to achieve the objectives of the study are designed questionnaire was distributed to a random sample of customer three private commercial banks in the city of Hama (BEMO bank - Bank of Syria and Almahjr- Arab Bank).
The use of pretrained language models, fine-tuned to perform a specific downstream task, has become widespread in NLP. Using a generic language model in specialized domains may, however, be sub-optimal due to differences in language use and vocabular y. In this paper, it is investigated whether an existing, generic language model for Swedish can be improved for the clinical domain through continued pretraining with clinical text. The generic and domain-specific language models are fine-tuned and evaluated on three representative clinical NLP tasks: (i) identifying protected health information, (ii) assigning ICD-10 diagnosis codes to discharge summaries, and (iii) sentence-level uncertainty prediction. The results show that continued pretraining on in-domain data leads to improved performance on all three downstream tasks, indicating that there is a potential added value of domain-specific language models for clinical NLP.
Unemployment is considered one of the most risky economic problems that faces the developing countries including Syria due to overpopulation, decreased investment growth, and capitals lack. Jeopardy of unemployment forwards as its negative conse quences overwhelm life all paces economic, social, political, and demographical …etc. As there are many solutions, small enterprise seems to be among the most realistic and reasonable out costing ones in comparison with the big projects that require huge capitals, advanced technology, and highly professional work mass. Furthermore, they are difficulty competent with their counterparts in the developed countries where there is no economic laboratory else than reality.
Earning calls are among important resources for investors and analysts for updating their price targets. Firms usually publish corresponding transcripts soon after earnings events. However, raw transcripts are often too long and miss the coherent str ucture. To enhance the clarity, analysts write well-structured reports for some important earnings call events by analyzing them, requiring time and effort. In this paper, we propose TATSum (Template-Aware aTtention model for Summarization), a generalized neural summarization approach for structured report generation, and evaluate its performance in the earnings call domain. We build a large corpus with thousands of transcripts and reports using historical earnings events. We first generate a candidate set of reports from the corpus as potential soft templates which do not impose actual rules on the output. Then, we employ an encoder model with margin-ranking loss to rank the candidate set and select the best quality template. Finally, the transcript and the selected soft template are used as input in a seq2seq framework for report generation. Empirical results on the earnings call dataset show that our model significantly outperforms state-of-the-art models in terms of informativeness and structure.
Neuroprosthesis can be used to restore lost motor functions for paraplegicsby using functional electrical stimulation (FES). Neuroprosthesis controllers determine the relationship between the stimulation pulses and joint angles to generate electric al stimulation patterns for the desired movement.To develop intelligent controllers, an inverse model which is the basic component of the intelligent controller is built by using empirical approaches to get a data set that consists of input (stimulation pulses) and output (joint angles). Because of the numerous exhausting experiments on patients and the need for repetition during Controller design, this study uses modeling and simulation to generate the data setthrough developing humanoid model, and simulating practical trials of quadriceps stimulation during swing leg movement. We connected three programs to develop a humanoid model by building: body segments in Visual Nastran 4D, muscles in Virtual Muscle 4.0.1, and passive joint properties in Matlab/ Simulink. Then the humanoid model was used to producethe identification data sets, through applying sinusoidal and random signals to simulate the stimulation of the knee extensors. The humanoid model can fit different users by using a number of graphical user interface screens to change the human and muscles parameters, so it is a generic model. It can be used in developing controllers to restore lost movement such as standing up, walking, jumping, etc. The simulation results is similar to practical trials, so using the developed model can reduce the number of experimental tests to be performed with patients during Neuroprosthesis controllers design.
comments
Fetching comments Fetching comments
Sign in to be able to follow your search criteria
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا